Jürgen Sturm

Sturm earned his bachelor's and master's degrees in Artificial Intelligence from the University of Amsterdam in 2006, followed by a PhD in Robotics from the University of Freiburg, with his later thesis published as a book in 2013.^[7] From 2011 to 2014, he served as a Postdoctoral Researcher in the Computer Vision group at the Technical University of Munich (TUM), where he worked on real-time camera tracking and 3D person scanning methods. Concurrently, he began his academic career, delivering lectures at TUM and teaching an online course at EdX in 2012 and 2013.^[8]

At TUM, Sturm developed a 3D reconstruction algorithm enabling 3D scanning of a person for printing as a small figure,^[9] leading to him co-founding the 3D scanning startup FabliTec in 2013, where he served as CEO until 2015.^[10] In 2014, he joined Metaio as a Senior Software Developer and Team Lead.^[11] Subsequently, he was appointed Senior Software Engineer and Tech Lead Manager at Google.^[12] leading to multiple patents.^[13][14] He assumed the position of an Engineering Manager at Intrinsic in 2019.^[1]

Sturm has contributed to the field of engineering by studying robotics, machine intelligence and machine perception, holding several patents for his developments in RGB-D cameras and 3D mapping techniques.^[2]

Sturm has researched and worked on RGB-D cameras throughout his career. In a collaborative effort, he presented a benchmark for RGB-D SLAM systems, offering high-quality image sequences with accurate ground truth camera poses, diverse scenes, and automatic evaluation tools accessible through a dedicated website.^[15] He also proposed a dense visual SLAM method for RGB-D cameras, alongside Daniel Cremers and Wolfram Burgard, improving pose accuracy by minimizing errors.^[16] Additionally, he showcased an RGB-D camera SLAM system for the Microsoft Kinect, assessing its accuracy, robustness, and speed across different indoor scenarios and offering it as open-source software.^[17]

Sturm's work on 3D mapping focused on reconstruction and improving techniques for precision. Alongside colleagues, he demonstrated a mapping system using RGB-D cameras for accurate 3-D mapping.^[18] He also introduced a real-time mapping system for RGB-D images using an octree structure to update a textured triangle mesh, enabling efficient memory usage for mobile or flying robots,^[19] as well as a new real-time visual odometry method for monocular cameras, achieving superior accuracy and speed by continuously estimating a semi-dense inverse depth map.^[20] Furthermore, he presented a 3D reconstruction algorithm based on Truncated Signed Distance Functions (TSDF), addressing the challenge of representing dynamic environments for robots, with a focus on continuous refinement of static maps and robust scene differencing.^[21]

In a joint research effort, Sturm proposed a graph-based method to calibrate sensor suites for accurate direct georeferencing of images from small unmanned aerial systems, addressing static offsets and in-flight calibration of intrinsic camera parameters.^[22]

Sturm has been involved in the development of models for 3D perception and scanning as well. He presented ScanComplete, a data-driven method using a generative 3D CNN model to predict complete 3D models with semantic labels from incomplete scans.^[23] In addition, he revealed a real-time RGB-D scene understanding method for mobile devices, combining incremental reconstruction, geometric segmentation, and semantic labeling.^[24]